code: def get_groundtruth_model(X, labels, n_clusters, **kwargs):
      # dummy model to show true label distribution
      class Dummy:
          def __init__(self, y):
              self.labels_ = labels
  
      return Dummy(labels)
  
imports: import gradio
  import math
  from functools import partial
  import matplotlib.pyplot
  import numpy
  from sklearn.cluster import AgglomerativeClustering, Birch, DBSCAN, KMeans, MeanShift, OPTICS, SpectralClustering, estimate_bandwidth
  from sklearn.datasets import make_blobs, make_circles, make_moons
  from sklearn.mixture import GaussianMixture
  from sklearn.neighbors import kneighbors_graph
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 9 for calling a global function with example usage: get_groundtruth_model(X, labels, n_clusters) and returns: Dummy